Gene expression profiling reveals candidate biomarkers and probable molecular mechanism in diabetic peripheral neuropathy
Gene expression profiling reveals candidate biomarkers and probable molecular mechanism in diabetic peripheral neuropathy
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基因表达谱揭示糖尿病周围神经病变的候选生物标志物和可能的分子机制
DOI：
10.2147/dmso.s209118
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发表时间：
2019-07
期刊：
影响因子：
--
通讯作者：
Zhang WenChuan
中科院分区：
文献类型：
--
作者：
Zhou Han;Zhang WenChuan
目的探讨糖尿病周围神经病变（DPN）的分子机制，寻找DPN基因表达谱的候选生物标志物。方法从GSE 24290数据集中筛选进展型与非进展型DPN患者的差异表达基因。进行功能富集分析，并从蛋白质-蛋白质相互作用网络中提取枢纽基因。获得另一数据集GSE 95849中血清样本中hub基因的表达水平，然后进行ROC曲线分析。结果从数据集GSE 24290中共获得352个DEG。它们涉及14个基因本体论术语和10个京都基因和基因组途径百科全书，主要与脂质代谢有关。揭示了8个枢纽基因（LEP、APOE、ADIPOQ、FABP 4、CD 36、GPAM、CIDEC和PNPLA 4），并在数据集GSE 95849中获得了它们的表达水平。受试者工作特征曲线分析表明，CIDEC（AUC=1）、APOE（AUC=0.833）、CD 36（AUC=0.803）和PNPLA 4（AUC=0.861）可能是DPN的候选血清标志物。结论进行性DPN时许旺细胞脂质代谢受到抑制。CIDEC、APOE、CD 36和PNPLA 4可能是早期诊断糖尿病周围神经病变的潜在生物标志物。
Purpose To investigate the molecular mechanism and search for candidate biomarkers in the gene expression profile of patients with diabetic peripheral neuropathy (DPN). Methods Differentially expressed genes (DEGs) of progressive vs non-progressive DPN patients in dataset GSE24290 were screened. Functional enrichment analysis was conducted, and hub genes were extracted from the protein–protein interaction network. The expression level of hub genes in serum samples in another dataset GSE95849 was obtained, followed by the ROC curve analysis. Results A total of 352 DEGs were obtained from dataset GSE24290. They were involved in 14 gene ontology terms and 10 Kyoto Encyclopedia of Genes and Genomes pathways, mainly related to lipid metabolism. Eight hub genes (LEP, APOE, ADIPOQ, FABP4, CD36, GPAM, CIDEC, and PNPLA4) were revealed, and their expression level was obtained in dataset GSE95849. The receiver operating characteristic curve analysis indicated that CIDEC (AUC=1), APOE (AUC=0.833), CD36 (AUC=0.803), and PNPLA4 (AUC=0.861) might be candidate serum biomarkers of DPN. Conclusion Lipid metabolism of Schwann cells might be inhibited in progressive DPN. CIDEC, APOE, CD36, and PNPLA4 might be potential predictive biomarkers in the early DPN diagnosis of patients with DM.
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影响因子：
5.1
作者：
Guariguata, L.;Whiting, D. R.;Shaw, J. E.
通讯作者：
Shaw, J. E.
PathView Web：用户友好的路径可视化和数据集成。
影响因子：
14.9
作者：
Luo W;Pant G;Bhavnasi YK;Blanchard SG Jr;Brouwer C
通讯作者：
Brouwer C
DOI：
10.1007/s00424-014-1452-z
发表时间：
2014-01
期刊：
Pflügers Archiv - European Journal of Physiology
影响因子：
--
作者：
S. Todorovic;V. Jevtovic-Todorovic
通讯作者：
S. Todorovic;V. Jevtovic-Todorovic
影响因子：
7.2
作者：
Salzer, James L.
通讯作者：
Salzer, James L.
影响因子：
8.2
作者：
Malik, RA;Tesfaye, S;Ward, JD
通讯作者：
Ward, JD